Study On The Ecolohy Environment Risk Analysis And Safety Assessment Methodology Of Transgenic Plants

With the commercial release of transgenic plants in large range, there are many potential and large risks of ecological environment. Currently, the risk analysis and safety assessment methods research of transgenic plants are still at the primary stage, and there are almost not effectual methods applied to agriculture practice. To build a system of risk analysis and safety assessment methods of transgenic plants, some preliminary study is developed in this paper, which the main contents were as following:Firstly, based on the combination of the causality of analysis with the fault tree analysis, the risk sources of transgenic plants were system idetified. According to the analysis results of causality analysis, gene flow was the most important reason among transgenic plants ecological environment risks. The basic events were analysised by fault tree analysis, in which, volunteer crops played an important role in structure importance. According to the result of system identification, the gene flow and volunteer crops were two main research contents in this paper.Secondly, to understand the gene flow rules of transgenic plants, the gene flow risk complex network analysis method was built based on the theory of complex network and small group. The method included four steps:transgenic plants gene flow network construction; network structure characteristics analysis; small group analysis and structure isomorphism analysis.The method was demonstraded based on the documents of normal rapeseed hybridizing with cruciferae from 1989 to 2008. The transgenic rapeseed gene flow topological graph was constructed and the structural characteristics were analyzed. The result showed that node degree of network followed power-law distribution and had the scale-free properties. The network robustness was analyzed from two aspects of random attacks and intentional attacks. Analysis showed the gene flow network was robust against random failures of nodes but fragile to intentional attacks when the removal of node no more than 10% nodes. At last, the subgroup and structural position were analyzed, which showed 22 kinds cruciferae plant were divided into two subgroups and five structural positions, and Brassica napus played a key role in subgroups and structural position. These research results can provide new approach for transgenic plants gene flow research.To further study on the risk rule of the transgenic plants based on the gene flow risk complex network analysis method, the gene flow risk ranking integration model was built based on TOPSIS ranking and rough set theory. Then, the model was demonstrated by using the cross combination documents and the biological characteristics data in China flora, the result showed the model can preferably identify the rank between Brassica napus and cruciferae and further deepened the results of the complex network analysis method.Two aspects research were mainly to be developed on safety assessment method. Firstly, to predict the law of vegetative growth of transgenic plants and study corresponding agricultural cultivation method when they compete with volunteer crops, an evaluation model of transgenic plants was proposed base on theory of barycenter of fuzzy set and entropy method. The model mainly included four steps:The normal membership function establishment of evaluation indexes, calculating index barycenter vector set by theory of barycenter of fuzzy set, calculating index weight by entropy method and identifying the vegetative growth rate rank. Subsequently, the evaluation model was demonstrated by using the cross data of normal rapeseed. These results proved that the model proposed could identify plants vegetative growth rate rank in various phonological phase and was operational. Furthermore, the agriculture activities of transgenic plants could be inducted by it. Secondly, to predict the environmental risk of the gene flow of transgenic plants after commercialization, a protocol for assessing its compatibility risks was proposed by the fuzzy clustering analysis and fuzzy model identification along with the biometric theory. The protocol included four steps:the fuzzy clustering analysis of interspecific crossing compatibility of transgenic plants, the F test of the outcome of the fuzzy clustering analysis, ranking of the risk of the interspecific crossing compatibility, and identifying the risk ranks. At the final stage of the protocol, various methods for identifying risk ranks were proposed to accommodate different data collection situations, therefore this approach was more flexible than the rigid ranking by the traditional clustering analysis. Subsequently, the protocol was demonstrated by using the the documents of normal rapeseed, and six ranks of risks were established, and the risk rank of the interspecific compatibility was identified successfully in a crossing data of Brassica napus. These results proved that the protocol proposed was operational.At last, based on these methods built above, the grid management pattern and some legislative suggestions of transgenic plants risk control were put forward.